The goal of this project is to advance understanding of how color is represented in cortex. While the first stages of color perception are well understood, much less is known about subsequent processing. The general aim of this proposal is to identify neural populations in cortex that support a second stage of processing, the opponent colors representation. Perceptual studies reveal that this representation encodes color as three combinations of cone signals, encoding relative amounts of red and green, blue and yellow, and light and dark. These perceptual mechanisms: 1) signal specific, linear combinations of cone signals; 2) maintain their color properties even as spatial pattern changes; 3) change their responsiveness independently of each other; 4) are selective for spatial frequency and orientation; 5) pass signals to other, non-cardinal color mechanisms. But the neural bases of opponent colors mechanisms remain unkown. While parvocellular neurons in the lateral geniculate nucleus receive opposing cone inputs, these cells fail to show properties 2 and 3, listed above. Some neurons in areas V2-V4 are tuned for non-cardinal colors, and are selective for spatial frequency, but the crucial experiments linking these neurons to perceptual results have not been performed. The work proposed here is designed to identify neural populations that can account for the opponent colors mechanisms. The responsiveness of human visual areas and LGN to stimuli of many colors will be measured using functional magnetic resonance imaging. A series of experiments will test for the 5 key properties of opponent color mechanisms. First, the linearity of color responses will be tested. Next, color responses will be measured at several spatial frequencies and in the presence of adapting stimuli, testing for properties 2, 3, and 5. Finally, measurements of transfer of adaptation will test for property 4. Visual areas whose responses show these properties are likely to contain populations of neurons that support color perception. Populations showing the different properties will most likely be found in different visual areas, helping to reveal the specific role of each area in the computations that underly color perception, and testing computational theories of color perception.